Senior Engineering Manager (People Analytics)

About the role

Join our team as a Senior Engineering Manager (People Analytics) where you will lead the data engineering function supporting People Analytics. This role requires hands-on technical leadership and people leadership, with a strong focus on business partnership. You will manage and develop a team of data engineers, create a strong engineering culture, collaborate with cross-functional teams, and own engineering standards. Additionally, you will support AI-enabled analytics and balance speed and rigor in your work. Key missions: Manage and develop a team of data engineers, setting expectations for quality, collaboration, delivery, and technical ownership.. Collaborate with cross-functional teams to translate requirements into production-ready deliverables, and communicate technical trade-offs to non-technical partners.. Lead the design, maintenance, and improvement of scalable People data foundations, including data models, pipelines, and testing frameworks. Profile: - Proven ability to coach engineers and build healthy technical culture - Experience with data quality, testing, lineage, observability, and production support - Strong analytical and problem-solving abilities, with the capability to simplify complex issues into actionable plans - Strong communication with technical and non technical stakeholders - A bachelor's degree in Computer Science, Data Science, Engineering, or a related field - 7+ years in data engineering, analytics engineering, or data platform engineering - Strong ability to translate business needs into technical architecture - Proficiency in data engineering tech stack: Python / SQL / dbt / Airflow / Gitlab - Proficiency in relational and cloud database platforms such as Snowflake, Redshift, or GCP - Thorough knowledge of data modeling, database design, data architecture principles, data operations, and CI/CD - Experience with sensitive or regulated data and access controls - 5+ years managing or formally leading engineers - Experience designing dimensional models, semantic layers, data marts, or analytical data products - People analytics, HR data, compensation, talent, workforce planning, or Workday experience - Experience in fintech, banking, or regulated environments - Experience with Snowflake Cortex AI, Streamlit, semantic models, or evaluation frameworks - Experience building AI, LLM, RAG, or natural language analytics products